Analysis of modulated spiking neural network

In seiner Bachelorarbeit hat Stefan Bruhns einen neuen Typ neuronaler Netzwerke namens “modulated spiking neural network” geschaffen. Diese Arbeit liefert eine vertiefende Analyse des neuen Netzwerkes, bei welcher das Netzwerk verschiedene Aufgaben losen muss. Zusatzlich wird die Leistung der modulated spiking neural network mit der anderer Netzwerktypen verglichen. In his Bachelor thesis Stefan Bruhns has created a new network type called “modulated spiking neural network”. This thesis expands his work by analysing the performance of the new network on different tasks and comparing them to different other network types.

[1]  Scott E. Fahlman,et al.  The Recurrent Cascade-Correlation Architecture , 1990, NIPS.

[2]  Patrick van der Smagt,et al.  Introduction to neural networks , 1995, The Lancet.

[3]  Randall D. Beer,et al.  On the Dynamics of Small Continuous-Time Recurrent Neural Networks , 1995, Adapt. Behav..

[4]  Bernard Widrow,et al.  Neural networks: applications in industry, business and science , 1994, CACM.

[5]  Nicholas T. Carnevale,et al.  Simulation of networks of spiking neurons: A review of tools and strategies , 2006, Journal of Computational Neuroscience.

[6]  Earl Cox,et al.  Fuzzy Modeling And Genetic Algorithms For Data Mining And Exploration , 2005 .

[7]  Eugene M. Izhikevich,et al.  Which model to use for cortical spiking neurons? , 2004, IEEE Transactions on Neural Networks.

[8]  Phil Husbands,et al.  Evolving Robot Behaviours with Diffusing Gas Networks , 1998, EvoRobot.

[9]  Phil Husbands,et al.  Better Living Through Chemistry: Evolving GasNets for Robot Control , 1998, Connect. Sci..

[10]  W. Baxt Application of artificial neural networks to clinical medicine , 1995, The Lancet.

[11]  J. D. Schaffer,et al.  Combinations of genetic algorithms and neural networks: a survey of the state of the art , 1992, [Proceedings] COGANN-92: International Workshop on Combinations of Genetic Algorithms and Neural Networks.

[12]  D. Edwards Data Mining: Concepts, Models, Methods, and Algorithms , 2003 .

[13]  A. Reber Implicit learning of artificial grammars , 1967 .

[14]  Thomas M. Smith,et al.  The evolvability of artificial neural net-works for robot control , 2002 .

[15]  Andrew Philippides,et al.  Temporally adaptive networks: Analysis of GasNet robot control. , 2002 .

[16]  Wofgang Maas,et al.  Networks of spiking neurons: the third generation of neural network models , 1997 .